I. Field of the Invention
The present invention generally relates to data processing and deployment systems and methods. More particularly, the invention relates to computerized systems and methods for automated parallelization of deployment in a supply chain environment.
II. Background Information
In a supply chain management (SCM) environment, Supply Network Planning (SNP) typically integrates the purchasing, manufacturing, distribution, and transportation of products so that comprehensive tactical planning and sourcing decisions can be simulated and implemented on the basis of a single, global consistent model. SNP, which may be implemented using software or computerized applications, uses advanced optimization techniques, based on constraints and penalties, to plan product flow along the supply chain. The result is optimal purchasing, production, and distribution decisions, reduced-order fulfillment times and inventory levels, and improved customer service.
Starting from a demand plan, SNP determines a permissible short-to medium-term plan for fulfilling the estimated sales volumes. This plan covers both the quantities that must be transported between locations (for example, a distribution center to a customer or a production plant to a distribution center), and the quantities to be produced and procured. When making a recommendation, SNP may compare all logistical activities to the available capacity.
Within SNP, a deployment application is often provided that calculates the quantity of products available to deploy from source locations to destination locations. The deployment application may determine how and when inventory should be deployed to distribution centers, customers, and vendor-managed inventory accounts. It produces optimized distribution plans based on constraints (such as transportation capacities) and business rules (such as minimum cost approach or replenishment strategies). A deployment application may create a distribution plan for one product at one location.
Currently, technology is available to help create distribution plans for products within a supply chain environment. However, existing deployment applications suffer from several drawbacks. One problem is that conventional deployment applications only deploy one product at a time from a source location to a destination location. As a result, a deployment application may have to run several times in order to deploy several products, even if the products are in the same source location. This leads to very long processing or run times as the products are processed successively.
Furthermore, in some existing deployment applications, a user may manually group the products into various packages and then start a deployment process for each of the packages at the same time. However, this often leads to severe errors in distribution. For example, if two processes were started for two packages, and each package contained the same product, a lock-up would occur with the processes if the quantity of the products in the packages exceeded the available quantity of the products.
Accordingly, there is a need for improved systems and methods for automatically and more efficiently process deployment runs, such as deployment runs in a supply chain environment.